Four dark corners of requirements engineering
ACM Transactions on Software Engineering and Methodology (TOSEM)
Mastering the requirements process
Mastering the requirements process
Program design by informal English descriptions
Communications of the ACM
Practical Software Maintenance: Best Practices for Managing Your Software Investment
Practical Software Maintenance: Best Practices for Managing Your Software Investment
AbstFinder, A Prototype Natural Language Text Abstraction Finder for Use in Requirements Elicitation
Automated Software Engineering
Measuring Similarity between Ontologies
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
The Stream Boiler Case Study: Competition of Formal Program Specification and Development Methods
Formal Methods for Industrial Applications, Specifying and Programming the Steam Boiler Control (the book grow out of a Dagstuhl Seminar, June 1995).
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Toward Rapid Ontology Development for Underdeveloped Domains
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 4 - Volume 4
Object-oriented COBOL recycling
WCRE '96 Proceedings of the 3rd Working Conference on Reverse Engineering (WCRE '96)
Lightweight Validation of Natural Language Requirements: A Case Study
ICRE '00 Proceedings of the 4th International Conference on Requirements Engineering (ICRE'00)
Automatic Acquisition of Hyponyms
Automatic Acquisition of Hyponyms
Attempto Controlled English (ACE)Language ManualVersion 3.0
Attempto Controlled English (ACE)Language ManualVersion 3.0
Maximum entropy models for natural language ambiguity resolution
Maximum entropy models for natural language ambiguity resolution
Ontology as a Requirements Engineering Product
RE '03 Proceedings of the 11th IEEE International Conference on Requirements Engineering
Finding parts in very large corpora
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
IWPC '05 Proceedings of the 13th International Workshop on Program Comprehension
Building automatically a business registration ontology
dg.o '02 Proceedings of the 2002 annual national conference on Digital government research
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Do we always use the same name for the same concept? Usually not. While misunderstandings are always troublesome, they pose particularly critical problems in software projects. Requirements engineering deals intensively with reducing the number and scope of misunderstandings between software engineers and customers. Software maintenance is another important task where proper understanding of the application domain is vital. In both cases it is necessary to gain (or regain) domain knowledge from existing documents that are usually inconsistent and imprecise. This paper proposes to reduce the risk of misunderstandings by unifying the terminology of the different stakeholders with the help of an ontology. The ontology is constructed by extracting terms and relations from existing documents. Applying text mining for ontology extraction has an unbeatable advantage compared to manual ontology extraction: Text mining detects terminology inconsistencies before they are absorbed in the ontology. In addition to this, the approach presented in this paper also introduces an explicit validation of ontology gained by text mining.